pr review - refactoring backtesting freqai

freqtrade/freqai/data_kitchen.py

@@ -1,7 +1,6 @@
 import copy
 import datetime
 import logging
-import os
 import shutil
 from pathlib import Path
 from typing import Any, Dict, List, Tuple
@@ -1108,15 +1107,25 @@ class FreqaiDataKitchen:
         :param file_name: h5 file name
         :param root_folder: folder to save h5 file
         """
-        os.makedirs(root_folder, exist_ok=True)
+        backtesting_root = Path(
-        append_df.to_hdf(file_name, key='append_df', mode='w')
+            self.full_path
+            / root_folder
+        )
+        if not backtesting_root.is_dir():
+            backtesting_root.mkdir(parents=True, exist_ok=True)
 
-    def get_backtesting_prediction(self, prediction_file_name: str) -> DataFrame:
+        full_file_path = Path(self.full_path / root_folder / file_name)
+        append_df.to_hdf(full_file_path, key='append_df', mode='w')
+
+    def get_backtesting_prediction(
+        self, root_prediction: str, prediction_file_name: str
+    ) -> DataFrame:
         """
         Retrive from disk the prediction dataframe
         :param prediction_file_name: prediction file full path
         :return:
         :Dataframe: Backtesting prediction from current backtesting period
         """
-        append_df = pd.read_hdf(prediction_file_name)
+        prediction_path = Path(self.full_path / root_prediction / prediction_file_name)
+        append_df = pd.read_hdf(prediction_path)
         return append_df

freqtrade/freqai/freqai_interface.py

@@ -234,12 +234,12 @@ class IFreqaiModel(ABC):
             if self.backtest_prediction_exists(
                 metadata["pair"], dk, trained_timestamp=trained_timestamp_int
             ):
-                prediction_filename, _ = self.get_backtesting_prediction_file_name(
+                prediction_filename, root_prediction = self.get_backtesting_prediction_file_name(
                     metadata["pair"],
                     dk,
                     trained_timestamp=int(trained_timestamp.stopts))
 
-                append_df = dk.get_backtesting_prediction(prediction_filename)
+                append_df = dk.get_backtesting_prediction(root_prediction, prediction_filename)
                 dk.append_predictions(append_df)
             else:
                 if not self.model_exists(
@@ -680,10 +680,10 @@ class IFreqaiModel(ABC):
         :boolean: whether the prediction file exists or not.
         """
         if not self.live:
-            prediction_file_name, _ = self.get_backtesting_prediction_file_name(
+            prediction_file_name, root_prediction = self.get_backtesting_prediction_file_name(
                 pair, dk, trained_timestamp
             )
-            path_to_predictionfile = Path(prediction_file_name)
+            path_to_predictionfile = Path(dk.full_path / root_prediction / prediction_file_name)
 
             file_exists = path_to_predictionfile.is_file()
             if file_exists and not scanning:
@@ -711,8 +711,8 @@ class IFreqaiModel(ABC):
         """
         coin, _ = pair.split("/")
         prediction_base_filename = f"{coin.lower()}_{trained_timestamp}"
-        root_prediction = f'{dk.full_path}/backtesting_predictions'
+        root_prediction = 'backtesting_predictions'
-        prediction_file_name = f"{root_prediction}/{prediction_base_filename}_predictions.h5"
+        prediction_file_name = f"{prediction_base_filename}_predictions.h5"
         return prediction_file_name, root_prediction
 
     # Following methods which are overridden by user made prediction models.

tests/freqai/test_freqai_interface.py

@@ -192,7 +192,7 @@ def test_start_backtesting(mocker, freqai_conf):
     freqai.start_backtesting(df, metadata, freqai.dk)
     model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
 
-    assert len(model_folders) == 5
+    assert len(model_folders) == 6
 
     shutil.rmtree(Path(freqai.dk.full_path))
 
@@ -217,7 +217,7 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf):
     metadata = {"pair": "LTC/BTC"}
     freqai.start_backtesting(df, metadata, freqai.dk)
     model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
-    assert len(model_folders) == 8
+    assert len(model_folders) == 9
 
     shutil.rmtree(Path(freqai.dk.full_path))
 
@@ -242,7 +242,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog):
     freqai.start_backtesting(df, metadata, freqai.dk)
     model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
 
-    assert len(model_folders) == 5
+    assert len(model_folders) == 6
 
     # without deleting the exiting folder structure, re-run
 
@@ -263,7 +263,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog):
     freqai.start_backtesting(df, metadata, freqai.dk)
 
     assert log_has_re(
-        "Found model at ",
+        "Found backtesting prediction ",
         caplog,
     )